An assessment of temperature and precipitation change projections over Italy from recent global and regional climate model simulations

2009 ◽  
Vol 30 (1) ◽  
pp. 11-32 ◽  
Author(s):  
Erika Coppola ◽  
Filippo Giorgi
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Precipitation Change ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Climate Model Simulations

scholarly journals Development of probability distributions for regional climate change from uncertain global mean warming and an uncertain scaling relationship

2007 ◽  
Vol 11 (3) ◽  
pp. 1097-1114 ◽  
Author(s):  
B. Hingray ◽  
A. Mezghani ◽  
T. A. Buishand
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Probability Distributions ◽  
Regional Climate ◽  
Natural Variability ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Climate Model Simulations ◽  
Global Mean

Abstract. To produce probability distributions for regional climate change in surface temperature and precipitation, a probability distribution for global mean temperature increase has been combined with the probability distributions for the appropriate scaling variables, i.e. the changes in regional temperature/precipitation per degree global mean warming. Each scaling variable is assumed to be normally distributed. The uncertainty of the scaling relationship arises from systematic differences between the regional changes from global and regional climate model simulations and from natural variability. The contributions of these sources of uncertainty to the total variance of the scaling variable are estimated from simulated temperature and precipitation data in a suite of regional climate model experiments conducted within the framework of the EU-funded project PRUDENCE, using an Analysis Of Variance (ANOVA). For the area covered in the 2001–2004 EU-funded project SWURVE, five case study regions (CSRs) are considered: NW England, the Rhine basin, Iberia, Jura lakes (Switzerland) and Mauvoisin dam (Switzerland). The resulting regional climate changes for 2070–2099 vary quite significantly between CSRs, between seasons and between meteorological variables. For all CSRs, the expected warming in summer is higher than that expected for the other seasons. This summer warming is accompanied by a large decrease in precipitation. The uncertainty of the scaling ratios for temperature and precipitation is relatively large in summer because of the differences between regional climate models. Differences between the spatial climate-change patterns of global climate model simulations make significant contributions to the uncertainty of the scaling ratio for temperature. However, no meaningful contribution could be found for the scaling ratio for precipitation due to the small number of global climate models in the PRUDENCE project and natural variability, which is often the largest source of uncertainty. In contrast, for temperature, the contribution of natural variability to the total variance of the scaling ratio is small, in particular for the annual mean values. Simulation from the probability distributions of global mean warming and the scaling ratio results in a wider range of regional temperature change than that in the regional climate model experiments. For the regional change in precipitation, however, a large proportion of the simulations (about 90%) is within the range of the regional climate model simulations.

scholarly journals Changes in Twentieth-Century Extreme Temperature and Precipitation over the Western United States Based on Observations and Regional Climate Model Simulations*

2013 ◽  
Vol 26 (21) ◽  
pp. 8556-8575 ◽  
Author(s):  
Valérie Dulière ◽  
Yongxin Zhang ◽  
Eric P. Salathé
Keyword(s):  
United States ◽  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Western United States ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Climate Model Simulations

Abstract Trends in extreme temperature and precipitation in two regional climate model simulations forced by two global climate models are compared with observed trends over the western United States. The observed temperature extremes show substantial and statistically significant trends across the western United States during the late twentieth century, with consistent results among individual stations. The two regional climate models simulate temporal trends that are consistent with the observed trends and reflect the anthropogenic warming signal. In contrast, no such clear trends or correspondence between the observations and simulations is found for extreme precipitation, likely resulting from the dominance of the natural variability over systematic climate change during the period. However, further analysis of the variability of precipitation extremes shows strong correspondence between the observed precipitation indices and increasing oceanic Niño index (ONI), with regionally coherent patterns found for the U.S. Northwest and Southwest. Both regional climate simulations reproduce the observed relationship with ONI, indicating that the models can represent the large-scale climatic links with extreme precipitation. The regional climate model simulations use the Weather Research and Forecasting (WRF) Model and Hadley Centre Regional Model (HadRM) forced by the ECHAM5 and the Hadley Centre Climate Model (HadCM) global models for the 1970–2007 time period. Comparisons are made to station observations from the Historical Climatology Network (HCN) locations over the western United States. This study focused on temperature and precipitation extreme indices recommended by the Expert Team on Climate Change Detection Monitoring and Indices (ETCCDMI).

scholarly journals Regional climate model simulations of North Atlantic cyclones: frequency and intensity changes

2008 ◽  
Vol 36 ◽  
pp. 1-16 ◽  
Author(s):  
T Semmler ◽  
S Varghese ◽  
R McGrath ◽  
P Nolan ◽  
S Wang ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
North Atlantic ◽  
Climate Model ◽  
Regional Climate ◽  
Model Simulations ◽  
Intensity Changes ◽  
Climate Model Simulations
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